The implementation of the regularized EM algorithm is modular, so that the modules that perform he regularized estimation of regression parameters (e.g., ridge regression and generalized cross-validation) can be exchanged for other regularization methods and other methods of determiningca regularization parameter. Per-Christian Hansen's Regularization Tools contain Matlab modules implementing a collection of regularization methods that can be adapted to fit into the framework of the EM algorithm. The generalized cross-validation modules of the regularized EM algorithm are adapted from Hansen's generalized cross-validation modules.

In the Matlab implementation of the regularized EM algorithm, more emphasis was placed on the modularity of the program code than on computational efficiency.
The regularized EM algorithm is currently being developed further under a project funded by the National Science Foundation'sPaleo Perspectives on Climate Change program

Installation

The program package consists of several Matlab modules. To install the programs, copy the package (available as a tar.gz-file) into a directory that is accessible by Matlab. Unpack the package using